Amal Raj

Deepak Akkil, Mowafak Allaham, Amal Raj et al.

Reliable evaluation of AI agents operating in complex, real-world environments requires methodologies that are robust, transparent, and contextually aligned with the tasks agents are intended to perform. This study identifies persistent shortcomings in existing AI agent evaluation practices that are particularly acute in web agent evaluation, as exemplified by our audit of WebVoyager, including task-framing ambiguity and operational variability that hinder meaningful and reproducible performance comparisons. To address these challenges, we introduce Emergence WebVoyager, an enhanced version of the WebVoyager benchmark that standardizes evaluation methodology through clear guidelines for task instantiation, failure handling, annotation, and reporting. Emergence WebVoyager achieves an inter-annotator agreement of 95.9\%, indicating improved clarity and reliability in both task formulation and evaluation. Applying this framework to evaluate OpenAI Operator reveals substantial performance variation across domains and task types, with an overall success rate of 68.6\%, substantially lower than the 87\% previously reported by OpenAI, demonstrating the utility of our approach for more rigorous and comparable web agent evaluation.

Amal Raj, Vivek Balachandran

Quantum computing often requires classical data to be supplied to execution environments that may not be fully trusted or isolated. While encryption protects data at rest and in transit, it provides limited protection once computation begins, when classical values are encoded into quantum registers. This paper explores data obfuscation for protecting classical values during quantum computation. To the best of our knowledge, we present the first explicit data obfuscation technique designed to protect classical values during quantum execution. We propose an obfuscation technique that encodes sensitive data into structured quantum representations across multiple registers, avoiding direct exposure while preserving computational usability. Reversible quantum operations and amplitude amplification allow selective recovery of valid encodings without revealing the underlying data. We evaluate the feasibility of the proposed method through simulation and analyze its resource requirements and practical limitations. Our results highlight data obfuscation as a complementary security primitive for quantum computing.